* Add benchmark details.

This commit is contained in:
Matthew Honnibal 2015-01-25 01:25:27 +11:00
parent 7770057174
commit 96c96696b8

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@ -216,10 +216,19 @@ spaCy gives you easy and efficient access to them, which lets you build all
sorts of use products and features that were previously impossible. sorts of use products and features that were previously impossible.
Efficiency Speed Comparison
---------- ----------------
.. table:: Efficiency comparison. See `Benchmarks`_ for details. **Set up**: 100,000 plain-text documents were streamed from an SQLite3
database, and processed with an NLP library, to one of three levels of detail
--- tokenization, tagging, or parsing. The tasks are additive: to parse the
text you have to tokenize and tag it. The pre-processing was not subtracted
from the times --- I report the time required for the pipeline to complete.
I report mean times per document, in milliseconds.
**Hardware**: Intel i7-3770 (2012)
.. table:: Efficiency comparison. Lower is better.
+--------------+---------------------------+--------------------------------+ +--------------+---------------------------+--------------------------------+
| | Absolute (ms per doc) | Relative (to spaCy) | | | Absolute (ms per doc) | Relative (to spaCy) |
@ -266,8 +275,8 @@ representations.
It's evaluated against the current best published systems, following the standard It's evaluated against the current best published systems, following the standard
methodologies. These evaluations show that it performs extremely well. methodologies. These evaluations show that it performs extremely well.
Accuracy Accuracy Comparison
-------- -------------------
.. table:: Accuracy comparison, on the standard benchmark data from the Wall Street Journal. .. table:: Accuracy comparison, on the standard benchmark data from the Wall Street Journal.